





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


_lowercase		:  Dict			       ={'configuration_swin': ['SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SwinConfig', 'SwinOnnxConfig']}


try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowercase		:  Optional[int]			       =[
		    'SWIN_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'SwinForImageClassification',
		    'SwinForMaskedImageModeling',
		    'SwinModel',
		    'SwinPreTrainedModel',
		    'SwinBackbone',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowercase		:  List[str]			       =[
		    'TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'TFSwinForImageClassification',
		    'TFSwinForMaskedImageModeling',
		    'TFSwinModel',
		    'TFSwinPreTrainedModel',
		]

if TYPE_CHECKING:
		from .configuration_swin import SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinConfig, SwinOnnxConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_swin import (
				    SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
				    SwinBackbone,
				    SwinForImageClassification,
				    SwinForMaskedImageModeling,
				    SwinModel,
				    SwinPreTrainedModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_swin import (
				    TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TFSwinForImageClassification,
				    TFSwinForMaskedImageModeling,
				    TFSwinModel,
				    TFSwinPreTrainedModel,
				)

else:
		import sys

		_lowercase		:  Dict			       =_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase    :   Tuple						=			{
    'configuration_luke': ['LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LukeConfig'],
    'tokenization_luke': ['LukeTokenizer'],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase    :   int						=			[
		    'LUKE_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'LukeForEntityClassification',
		    'LukeForEntityPairClassification',
		    'LukeForEntitySpanClassification',
		    'LukeForMultipleChoice',
		    'LukeForQuestionAnswering',
		    'LukeForSequenceClassification',
		    'LukeForTokenClassification',
		    'LukeForMaskedLM',
		    'LukeModel',
		    'LukePreTrainedModel',
		]


if TYPE_CHECKING:
		from .configuration_luke import LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP, LukeConfig
		from .tokenization_luke import LukeTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_luke import (
				    LUKE_PRETRAINED_MODEL_ARCHIVE_LIST,
				    LukeForEntityClassification,
				    LukeForEntityPairClassification,
				    LukeForEntitySpanClassification,
				    LukeForMaskedLM,
				    LukeForMultipleChoice,
				    LukeForQuestionAnswering,
				    LukeForSequenceClassification,
				    LukeForTokenClassification,
				    LukeModel,
				    LukePreTrainedModel,
				)

else:
		import sys

		lowercase    :   Any						=			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)